Designing Bent Boolean Functions With Parallelized Linear Genetic Programming

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F17%3APU126400" target="_blank" >RIV/00216305:26230/17:PU126400 - isvavai.cz</a>

Result on the web

<a href="https://www.fit.vut.cz/research/publication/11402/" target="_blank" >https://www.fit.vut.cz/research/publication/11402/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3067695.3084220" target="_blank" >10.1145/3067695.3084220</a>

Result language

angličtina

Original language name

Designing Bent Boolean Functions With Parallelized Linear Genetic Programming

Original language description

Bent Boolean functions are cryptographic primitives essential for the safety of cryptographic algorithms, providing a degree of non-linearity to otherwise linear systems. The maximum possible non-linearity of a Boolean function is limited by the number of its inputs, and as technology advances, functions with higher number of inputs are required in order to guarantee a level of security demanded in many modern applications. Genetic programming has been successfully used to discover new larger bent Boolean functions in the past. This paper proposes the use of linear genetic programming for this purpose. It shows that this approach is suitable for designing of bent Boolean functions larger than those designed using other approaches, and explores the influence of multiple evolutionary parameters on the evolution runtime. Parallelized implementation of the proposed approach is used to search for new, larger bent functions, and the results are compared with other related work. The results show that linear genetic programming copes better with growing number of function inputs than genetic programming, and is able to create significantly larger bent functions in comparable time.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GA16-08565S" target="_blank" >GA16-08565S: Advancing cryptanalytic methods through evolutionary computing</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

GECCO Companion '17 Proceedings of the Companion Publication of the 2017 on Genetic and Evolutionary Computation Conference

ISBN

978-1-4503-4939-0

ISSN

—

e-ISSN

—

Number of pages

8

Pages from-to

1825-1832

Publisher name

Association for Computing Machinery

Place of publication

Berlín

Event location

Berlin

Event date

Jul 15, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000625865500309